MétaCan
Menu
Back to cohort
Record W2542048154 · doi:10.1109/camap.2005.1574181

Distributed Space-Time Block Coding for Cooperative Networks with Multiple-Antenna Nodes

2006· article· en· W2542048154 on OpenAlex
Simon Yiu, Robert Schober, Lutz Lampe

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpace–time block codeRelayNode (physics)Block codeSpace–time codeComputer scienceCoding (social sciences)Diversity gainBlock (permutation group theory)Antenna (radio)Topology (electrical circuits)Decoding methodsMathematicsMIMOAlgorithmBeamformingCombinatoricsTelecommunicationsPhysicsPower (physics)

Abstract

fetched live from OpenAlex

We present an extension to our previous work on distributed space-time block coding where we considered cooperative networks with a large set of single-antenna decode-and-forward relays N. Here, we consider the general case where each relay node is equipped with N/sub T/ antennas and the destination node has N/sub R/ antennas. It is assumed that at any given time only a small, a priori unknown subset of nodes S C N is active. In the proposed scheme, the signal transmitted by an active node is the product of an information-carrying space-time block code (STBC) matrix, which is identical for all nodes, and a unique node signature matrix. It is shown that existing STBCs designed for N/sub c/ /spl ges/ 2 co-located antennas are a favorable choice for the code matrix guaranteeing a diversity order of d = min {N/sub c/N/sub R/, N/sub T/N/sub S/N/sub R/} if ns nodes are active. Simulation results show that a considerable gain can be achieved by using multiple-antenna nodes even if the antennas are highly correlated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.240
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it